دانلود رایگان مقاله انگلیسی شناسایی جغرافیای سازگاری خرید آنلاین در بلژیک - الزویر 2018

ABSTRACT

The widespread adoption of the internet as retail channel is impacting a range of stakeholders. Retailers are expected to sell online, logistics operators are required to reconfigure their supply chain and public authorities try to keep local retail competitive while simultaneously attempt to manage the increase in freight transport. Within this context, a growing body of research is studying the socio-economic profile of the online shopper and the spatial variation in the demand for B2C goods. Yet, as can be expected for a relatively new evolution, little consensus exist. Therefore, in this paper, with data from the national retail federation on online shopping behaviour, we add to this growing field by first analysing the relation between socio-economic characteristics and the willingness to shop online. By mapping these characteristics, we then construct the geography of online shopping adoption in Belgium. Finally, we assess the impacts of this specific geography for the stakeholders that are adapting to this new reality. We conclude firstly that the well-educated man in his thirties with a well-paid job has the highest probability to shop online, independent of the level of urbanisation of the area he resides. Secondly, we predict over- and underestimations of the potential online buyers of up to 50% when assuming a homogeneous e-commerce penetration, especially in poorer urban areas. This implies a serious negligence for ecommerce practitioners and academics when ignoring the specific geography of the online shopping adoption.

Conclusions

In this paper, we seek to provide insights into the spatial distribution of the demand for B2C e-commerce and its implications for sustainability analyses. Two research questions arise. Who is the online shopper? And where does he or she live? This learns us the extent to which the demand for e-commerce is proportional to the distribution of the population, as is often assumed. The case study area is Belgium. We are able to provide an answer to the two research questions by analysing the dataset resulting from an online survey of over 1500 respondents concerning online shopping conducted by the Belgian retail federation (Comeos, 2016). First, the application of a logit regression allows the identification of the socio-economic variables that have a significant influence on the probability one shops online in Belgium. Similar to other studies in the Netherlands and the UK, the well-educated man in his thirties with a well-paid job has the highest probability to shop online. Whether this profile's shopping probability is due to time constraints, as proposed by Farag et al. (2007), or other incentives remains under study. Further, we found the urbanisation level of an area does not have a significant impact on the shopping probability. This could be due to the historical lack of urban planning in the country, resulting in relatively high shopping accessibility throughout Belgium, which turns the efficiency hypothesis (Anderson et al., 2003) invalid in our case.